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Plos One|July 31, 2009
Local network topology in human protein interaction data predicts functional associationHua Li, Shoudan LiangProceedings. IEEE Computer Society Bioinformatics Conference|February 3, 2006
cWINNOWER algorithm for finding fuzzy DNA motifsShoudan LiangBMC Bioinformatics|October 23, 2012
dsPIG: a tool to predict imprinted genes from the deep sequencing of whole transcriptomesHua Li, Xiao Su, Juan Gallegos, et al.Plos One|July 10, 2015
PAND: A Distribution to Identify Functional Linkage from Networks with Preferential Attachment PropertyHua Li, Pan Tong, Juan Gallegos, et al.Proceedings of the National Academy of Sciences of the United States of America|October 21, 2003
Predicting protein functions from redundancies in large-scale protein interaction networksManoj Pratim Samanta, Shoudan LiangBMC Bioinformatics|January 17, 2013
Accuracy of RNA-Seq and its dependence on sequencing depthGuoshuai Cai, Hua Li, Yue Lu, et al.BMC Bioinformatics|August 11, 2017
Local sequence and sequencing depth dependent accuracy of RNA-seq readsGuoshuai Cai, Shoudan Liang, Xiaofeng Zheng, et al.Genomics|January 8, 2008
Cell cycle-dependent nucleosome occupancy at cohesin binding sites in yeast chromosomesJie Liu, Daniel M Czajkowsky, Shoudan Liang, et al.Statistics in Biosciences|July 21, 2015
Bayesian Hierarchical Model for Differential Gene Expression Using RNA-seq DataJuhee Lee, Yuan Ji, Shoudan Liang, et al.Circulation. Cardiovascular Genetics|June 11, 2013
Toward breaking the histone code: bayesian graphical models for histone modificationsRiten Mitra, Peter Müller, Shoudan Liang, et al.Pageof 1,100